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  2. Generative adversarial network - Wikipedia

    en.wikipedia.org/wiki/Generative_adversarial_network

    GANs can be regarded as a case where the environmental reaction is 1 or 0 depending on whether the first network's output is in a given set. [109] Other people had similar ideas but did not develop them similarly. An idea involving adversarial networks was published in a 2010 blog post by Olli Niemitalo. [110]

  3. Wasserstein GAN - Wikipedia

    en.wikipedia.org/wiki/Wasserstein_GAN

    The Wasserstein Generative Adversarial Network (WGAN) is a variant of generative adversarial network (GAN) proposed in 2017 that aims to "improve the stability of learning, get rid of problems like mode collapse, and provide meaningful learning curves useful for debugging and hyperparameter searches".

  4. Adversarial machine learning - Wikipedia

    en.wikipedia.org/wiki/Adversarial_machine_learning

    Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. [1] A survey from May 2020 revealed practitioners' common feeling for better protection of machine learning systems in industrial applications.

  5. StyleGAN - Wikipedia

    en.wikipedia.org/wiki/StyleGAN

    The Style Generative Adversarial Network, or StyleGAN for short, is an extension to the GAN architecture introduced by Nvidia researchers in December 2018, [1] and made source available in February 2019.

  6. SANS Institute - Wikipedia

    en.wikipedia.org/wiki/SANS_Institute

    The courses cover security fundamentals and technical aspects of information security. The institute has been recognized for its training programs [3] and certification programs. [4] Per 2021, SANS is the world’s largest cybersecurity research and training organization. [5] SANS is an acronym for SysAdmin, Audit, Network, and Security. [6]

  7. Synthetic media - Wikipedia

    en.wikipedia.org/wiki/Synthetic_media

    Synthetic media (also known as AI-generated media, [1] [2] media produced by generative AI, [3] personalized media, personalized content, [4] and colloquially as deepfakes [5]) is a catch-all term for the artificial production, manipulation, and modification of data and media by automated means, especially through the use of artificial intelligence algorithms, such as for the purpose of ...

  8. Explainable artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Explainable_artificial...

    Marvin Minsky et al. raised the issue that AI can function as a form of surveillance, with the biases inherent in surveillance, suggesting HI (Humanistic Intelligence) as a way to create a more fair and balanced "human-in-the-loop" AI. [61] Explainable AI has been recently a new topic researched amongst the context of modern deep learning.

  9. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Dean Pomerleau uses a neural network to train a robotic vehicle to drive on multiple types of roads (single lane, multi-lane, dirt, etc.), and a large amount of his research is devoted to extrapolating multiple training scenarios from a single training experience, and preserving past training diversity so that the system does not become ...